Search results
Results from the WOW.Com Content Network
The key focus areas of data governance include availability, usability, consistency, data integrity and security, and standards compliance. The practice also includes establishing processes to ensure effective data management throughout the enterprise, such as accountability for the adverse effects of poor data quality, and ensuring that the ...
A data steward ensures that each assigned data element: Has clear and unambiguous data element definition; Does not conflict with other data elements in the metadata registry (removes duplicates, overlap etc.) Has clear enumerated value definitions if it is of type Code; Is still being used (remove unused data elements)
However, data has to be of high quality to be used as a business asset for creating a competitive advantage. Therefore, data governance is a critical element of data collection and analysis since it determines the quality of data while integrity constraints guarantee the reliability of information collected from data sources.
Information governance goes beyond retention and disposition to include privacy, access controls, and other compliance issues. In electronic discovery, or e-discovery, relevant data in the form of electronically stored information is searched for by attorneys and placed on legal hold. IG includes consideration of how this data is held and ...
Data Quality (DQ) is a niche area required for the integrity of the data management by covering gaps of data issues. This is one of the key functions that aid data governance by monitoring data to find exceptions undiscovered by current data management operations.
The Data Owner is responsible for the requirements for data definition, data quality, data security, etc. as well as for compliance with data governance and data management procedures. The Data Owner should also be funding improvement projects in case of deviations from the requirements.
Data architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. [1] Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture. [2]
Information assurance (IA) is the practice of assuring information and managing risks related to the use, processing, storage, and transmission of information. Information assurance includes protection of the integrity, availability, authenticity, non-repudiation and confidentiality of user data. [1]